Evaluation of GIS and Interpolation Methods in Determination of Spatial Distribution and Classified Groundwater Quality

Document Type : Technical Note (5 pages)

Authors

1 PhD Student in Water Engineering Department, Lorestan University, Khoramabad, Iran.

2 Associate Professor, Water Engineering Department, Lorestan University, Khoramabad, Iran.

3 Assistant Professor, Water Engineering Department, Lorestan University, Khoramabad, Iran.

Abstract

Groundwater is the most important water resource in arid and semiarid areas. Therefore, groundwater pollution is also important. In this study, spatial distribution of groundwater quality was evaluated in Shoor River basin in Dehaghan County, south of Esfahan Province. For this propose, Kriging, Cokriging and IDW methods were used to predicting spatial distribution of groundwater quality parameters related to 48 wells and Qanats. According to Anderson Darling test, data of water quality weren’t normal distributed, so, they were became normal by COX-BOX transformation. After that, variograme of each parameter was drawn for fitting the best interpolation model. Then, spatial distribution maps of groundwater quality were drawn by ArcGIS. Result showed that, ordinary Kriging was the best interpolation method for most of parameters. According to spatial distribution maps, pollution was aggregated in north of basin that its agreed with hydro geology condition in basin. Also spatial distribution of water quality index (WQI) was determined in area according to Water Health Organization Standard.

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Babaei Bazkiyaei Z, Shariati F, oshaksaraei L, and Amiri E (2013) Evaluation of groundwater quality and its suitability for drinking and agriculture use. Journal Agriculture and Crop Sciences 5:51-63
Baba A, and Tayfur G (2011) Groundwater contamination and its effect on health in Turkey. Journal of Environmental Monitoring and Assessment 83:77–94
Choi HM, and Lee JY (2011) Groundwater contamination and natural attenuation capacity at a petroleum spilled facility in Korea. Journal of Environmental Sciences 23(10):1650-1659
Poorfarahabadi E, and Kholghi M (2016) Evaluation of cokriging and neuro-fuzzy model performance in estimating the nitrate concentration in Karaj Aquifer. Journal of Iran- Water Resources Research 11(3):182-186 (In Persian)
Hamzaoui-Azaza F, Ketata M, Bouhlila R, Gueddari M, and Riberio L (2011) Hydro geochemical characteristics and assessment of drinking water quality in Zeuss– Koutine aquifer southeastern Tunisia. Journal of Environmental Monitoring and Assessment 174:283-298
Li PY, Qian H, and Wu JH (2010a) Groundwater quality assessment based on improved water quality index in Pengyang County Ningxia Northwest China. Journal of Chemistry 7(1):209-216
Momeni Damaneh J, Joulaei F, Alidadi H, and Peiravi R (2015) Evaluation of interpolation methods to determine spatial variations of groundwater qualitative parameters in Gonabad plain. Iranian Journal of Research in Environmental Health1 (3):165-176 (In Persian)
Riahi Madvar H, and Seifi A (2016) Spatial grouping analysis and fuzzy spatial analysis of Shahr-e-Babak plain groundwater quality for drinking and irrigation. Journal of Iran- Water Resources Research 12(2):152-157 (In Persian)
Stigter TY, Ribeiro L, and Carvalho Dill AMM (2006) Application of a groundwater quality index as an assessment and communication tool in agro-environmental policies a two Portuguese case studies. Journal of Hydrology 327(3-4):578-591
World Health Organization (WHO) (1998) Guide lines for drinking water 2nd edition health criteria and other information genera. Switzerland 2:281-308
Wu JH, Li PY, and Qian H (2011) Groundwater quality in Jingyuan County a semi-Humid area in northwest China. Journal of Chemistry 8(2):787-793